Intelligent fault diagnosis of water supply network based on ELM
Shifeng Yang · Jisuanji gongcheng yu sheji · 2013
To improve the generalization performance of the traditional extreme learning machine,an extreme learning machine model optimized is presented by artificial bee colony algorithm.The global optimization ability of artificial bee colony algorithm is combined with quick learning ability of extreme learning machine in this model,and the over-fitting phenomenan in traditional extreme learning machine are overcome efficaciously.On the basis of choosing the relative change value of water pressure as characteristic parameter,the optimized extreme learning machine model is applied to leakage fault diagnosis experiment of water supply network,and experimental results show that the fault diagnosis speed and precision of optimized extreme learning machine based on artificial bee colony algorithm are better than the other three models.